Nearly 90% of enterprises are still experimenting with GenAI, but most lack the security controls to manage it, creating prime opportunities for attackers.
50%
By 2026, organizations that adopt strong runtime protections will cut inaccurate or manipulated AI outputs in half, reducing both operational and regulatory risks.
Challenge
AI in mobile apps brings new risks
AI is no longer just in the cloud. It now lives inside mobile apps. This shift powers real-time personalization and smarter decisions, but it also puts models, data, and logic within reach of attackers.
If AI runs in your app, so do the risks.
Traditional app security wasn’t built for this new reality. On-device AI becomes part of the attack surface, exposed to theft, tampering, and manipulation.
Tampering with AI logic at runtime
Attackers can alter AI logic during execution by injecting code or modifying memory. The result? Distorted outputs and unsafe decisions. In finance, this could mean overriding loan approvals. In healthcare, it could mean corrupted medical advice. Conventional mobile security is not powerful enough to prevent tampering at runtime
AI model theft and IP loss
AI models represent years of investment in data and training. Once embedded, they can be extracted or cloned using reverse engineering tools. Stolen models fuel competitors, violate privacy, and erode your market edge. Protecting AI as critical IP is now a business necessity.
Prompt injection and input/output manipulation
Large Language Models (LLMs) and agentic AI are vulnerable to crafted inputs that hijack logic or exfiltrate data. In regulated sectors, manipulated outputs can lead to fraud, compliance violations, or customer harm. Protecting the input and output pathways of AI is essential to maintaining trust.
Business outcomes
Security that drives adoption
Ensure your AI-powered apps are resilient, compliant, and protected, allowing you to scale safely.
Protect your intellectual property
Your AI models are critical IP. Promon’s obfuscation, anti-debugging, and runtime protections make them extremely difficult to reverse engineer or steal. By safeguarding embedded models, you keep competitors from replicating your capabilities and ensure your investment remainstruly yours.
Stay resilient
Attacks that compromise AI behavior can cause downtime, service interruptions, or unsafe outputs. Promon prevents runtime tampering, code injection, and malicious interference, ensuring that AI systems continue operating as intended. This resilience is essential for high-stakes industries like finance, healthcare, and gaming.
Accelerate secure AI deployment
Embedding AI shouldn’t mean slowing down development. Promon integrates post-compile, requiring no source code access and minimal developer effort. This means product and engineering teams can ship new AI-driven features quickly, knowing runtime protection is automatically in place.
Simplify compliance
AI regulation is tightening. The EU AI Act, GDPR, NIST, and ISO/IEC 42001 demand robustness, tamper resistance, and data protection. Promon gives organizations the in-app controls and runtime visibility to prove compliance, lower audit costs, and reduce regulatory risk.
Who needs AI protection?
Finance and banking
Secure virtual assistants, fraud detection, and decision models that must remain trustworthy and compliant.
Gaming
Protect NPC logic, personalization engines, and anti-cheat systems from tampering and reverse engineering.
Healthcare
Safeguard diagnostic tools and AI-driven triage systems from manipulation and data leakage.
Any industry embedding agentic AI into apps
From retail to AR/VR, AI-driven features bring innovation and new attack surfaces. If your app makes decisions locally, attackers will try to exploit them.
Solution
How Promon secures on-device AI
Promon takes a layered approach to securing AI models and their runtime environments.
Model and IP protection
Use Promon to make it difficult for attackers to extract or reverse engineer embedded models. Through obfuscation, encryption, and anti-debugging, ensure that proprietary AI assets remain secure, even when deployed on user devices.
Runtime security
Protect your embedded AI models at app runtime. By deploying Promon, you can block dynamic code injection, tampering, and unauthorized execution. Even if an attacker gains root access or uses advanced instrumentation, Promon shields the AI logic from manipulation.
Input/output safeguarding
Prompt injection and input/output manipulation are growing attack vectors. Promon ensures that input validation mechanisms can’t be disabled and that responses can’t be intercepted or corrupted, protecting the integrity of AI decisions.
Product
The Promon AI security stack
Promon delivers AI protection through four complementary solutions.
Promon SHIELD™
Provides runtime integrity and tamper protection to secure both the app and its AI components.
What’s the difference between cloud AI and on-device AI?
Cloud AI models (like ChatGPT) run on servers and return results over the internet. On-device AI models live inside the app on a phone or endpoint. Promon focuses on on-device AI, because that’s where attackers can directly tamper with logic, steal models, or manipulate inputs/outputs.
What types of AI models are most at risk?
All models on-device are vulnerable, but GenAI and multimodal AI are particularly susceptible to prompt injection and input/output (I/O) manipulation. Predictive and decision models are often the biggest targets for IP theft and tampering.
How does Promon protect against model theft?
Promon combines code obfuscation, encryption, anti-debugging, and attestation to make models extremely hard to extract or clone. This protects IP investments and prevents competitors or attackers from stealing valuable AI assets.
What is agentic AI and why does it matter?
Agentic AI refers to autonomous AI agents that plan, decide, and act within apps. Unlike simple models, they execute workflows and interact with other systems. If compromised, attackers can hijack agents to exfiltrate data, manipulate goals, or run malware. Promon shields the runtime environment to stop this.
Can attackers use AI to attack or deobfuscate my AI models?
Large Language Models (LLMs) are being tested for code deobfuscation, but research shows they fail against advanced or combined obfuscation techniques. Simple obfuscation can sometimes be bypassed, but Promon uses layered protections (obfuscation, anti-tampering, runtime protection), which remain highly effective.
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